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const axios = require('axios');
const fs = require('fs');
const path = require('path');
// helper function to help you convert your local images into base64 format
async function toB64(imgPath) {
const data = fs.readFileSync(path.resolve(imgPath));
return Buffer.from(data).toString('base64');
}
const api_key = "YOUR API-KEY";
const url = "https://api.segmind.com/v1/gpt-5-mini";
const data = {
"messages": [
{
"role": "user",
"content" : "tell me a joke on cats"
},
{
"role": "assistant",
"content" : "here is a joke about cats..."
},
{
"role": "user",
"content" : "now a joke on dogs"
},
]
};
(async function() {
try {
const response = await axios.post(url, data, { headers: { 'x-api-key': api_key } });
console.log(response.data);
} catch (error) {
console.error('Error:', error.response.data);
}
})();Attributes
An array of objects containing the role and content
Could be "user", "assistant" or "system".
A string containing the user's query or the assistant's response.
To keep track of your credit usage, you can inspect the response headers of each API call. The x-remaining-credits property will indicate the number of remaining credits in your account. Ensure you monitor this value to avoid any disruptions in your API usage.
GPT-5 Mini: Multi-Modal Language Model
Edited by Segmind Team on October 28, 2025.
What is GPT-5 Mini?
GPT-5 Mini is a streamlined and compact version of OpenAI’s GPT-5 model, that is capable of performing fast reasoning and efficient processing. It is an advanced language model that merges GPT-5’s instruction-following capabilities with high-end performance. It also supports multi-modal inputs, such as text, images, and files, while maintaining high-quality text outputs. It is a reliable choice for developers when they need quick, consistent AI responses without the heavy computational load of large models.
Key Features of GPT-5 Mini
- It supports multi-modal input, including text, images, and files
- It is optimized for low-latency responses
- It has advanced instruction-following capabilities
- It has built-in safety features from GPT-5
- It is integrated with OpenAI API compatibility
- It comes with Azure integration support
- It offers streamlined architecture for efficient processing
Best Use Cases
- Real-time chatbots and virtual assistants
- Content analysis and summarization
- Image-enhanced text generation
- Educational technology applications
- Customer service automation
- Document processing and analysis
- Rapid prototyping of AI features
Prompt Tips and Output Quality
- Provide prompts with precise and detailed information for better results
- Utilize text and images (when needed) to provide clear context
- Structure complex queries into clear, separate instructions
- Specify relevant context for more accurate responses
- Frame questions precisely for analysis tasks
- Use high-resolution images for more detailed outputs
FAQs
How does GPT-5 Mini differ from standard GPT-5? GPT-5 Mini focuses on speed and efficiency while maintaining core GPT-5 capabilities. It is designed for lighter tasks based on reasoning to execute responses faster, making it ideal for applications requiring quick processing.
Is GPT-5 Mini available through multiple providers? Yes, GPT-5 Mini can be accessed through OpenAI's API and Azure, offering flexibility in deployment options.
Can GPT-5 Mini process multiple types of input? It generates text-based outputs from multi-modal inputs, including text, images, and files.
What are the best practices for prompt engineering with GPT-5 Mini? Provide clear, specific instructions and include relevant context. For multi-modal inputs, use high-resolution images relevant to the query.
How can developers integrate GPT-5 Mini into existing applications? GPT-5 can be integrated through standard OpenAI-compatible APIs, making it accessible to developers familiar with OpenAI's ecosystem.
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